It's not that any particular accent is "more satisfactory" per se, but rather that a system will work better on accents broadly close to those that it has been trained on.
Speech recognition is essentially a statistical process: the system pulls in various acoustic cues and then tries to predict which word/sequence of words is the statistically most likely, given its "knowledge" of which acoustic cues in which combinations tend to indicate which speech sounds. It's difficult to say in advance for a particular utterance which feature(s) will be more prevalent in that prediction: it depends on the particular utterance and on the training data. So it's difficult to point to a specific feature of a particular accent in isolation that will be more or less satisfactory: the system is really much more complex than that. (I disagree from that point of view with Peter Shor's comment above: I don't think you can be so specific as to point to one particular feature and then say "that's the best accent" overall.)
If you're interested more in the subject, then I'd recommend introductions to speech recognition such as you'll find in:
- Jurafsky & Martin, "Speech and Language Processing"
- The Oxford Handbook of Computational Linguistics
- Russel & Norvig, "Artificial Intelligence: A Modern Approch"